Dear mixOmics users,
Our new update 6.2.0 is now available on CRAN as part of our new version of our manuscript.
manuscript & package update:
The mixOmics manuscript introducing the supervised and integrative frameworks (PLS-DA, DIABLO block.plsda and MINT) has be updated, along with all the R / Sweave case studies, manuscript and codes are available at this link. The case studies are also published on our website (sPLSDA:SRBCT, Case study: TCGA and Case study: MINT).
The manuscript describes in more details the difference prediction distances (see also the supplemental material) and the interpretation of the AUROC for our supervised methods.
The constraint argument was removed from all our methods, due to a risk of overfitting.
– The constraint argument (version 6.1.0 – 6.1.3) was removed in the functions perf and tune for all supervised objects because of a risk of overfitting
– AUROC aded for MINT objects mint.plsda and mint.splsda where the study name needs to be specified, e.g. auroc( .., roc.study = “study4”). See ?auroc
– choice.ncomp output added on all perf and tune functions for all supervised methods.
– mat.c output for pls and plsda objects (matrix of coefficients from the regression of X / residual matrices X on the X-variates).
Bug fixes (thank you to the users who notified us on bitbucket):
– fixed bug when using predict, perf or tune with the error msg: ‘Error in predict.spls(spls.res, X.test[, nzv]) : ‘newdata’ must include all the variables of ‘object$X”
We advertised two workshops at this link. The advanced workshop 23-24 Oct 2017 is fully subscribed. This is our first MAW (mixOmics advanced workshop), but there will be more planned in 2018. We still have a few spots left for the classic workshop on the 9-10 Nov 2017 in Toulouse, contact us for more information (priority will be given to students and early career researchers).
Two senior postdoc positions (2 year and 3 year) still open!
The Australian mixOmics team now based at the University of Melbourne is recruiting two senior postdocs in the fields of computational biology or statistics, 1 full time 2-year position to work with the Stemformatics team on exciting omics integrating problems (‘omics and single cell omics) to improve stem cell classification, and 1 full time 3-year position for innovative multivariate methods developments for ‘omics time course, microbiome and P-integration. Contact us for more information.
With the invaluable help from the bioinformatics masters students Danielle Davenport and Zoe Welham we are currently revamping the website to ensure all codes are running correctly. Thank you for those who sent us some feedback!